Instructions to use VladHong/llama-cpp-K2-FAST2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use VladHong/llama-cpp-K2-FAST2 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf VladHong/llama-cpp-K2-FAST2 # Run inference directly in the terminal: llama cli -hf VladHong/llama-cpp-K2-FAST2
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf VladHong/llama-cpp-K2-FAST2 # Run inference directly in the terminal: llama cli -hf VladHong/llama-cpp-K2-FAST2
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf VladHong/llama-cpp-K2-FAST2 # Run inference directly in the terminal: ./build/bin/llama cli -hf VladHong/llama-cpp-K2-FAST2
Use Docker
docker model run hf.co/VladHong/llama-cpp-K2-FAST2
- Llama new
- LM Studio
- Jan
- Ollama
How to use VladHong/llama-cpp-K2-FAST2 with Ollama:
ollama run hf.co/VladHong/llama-cpp-K2-FAST2
- Unsloth Desktop
- Docker Model Runner
How to use VladHong/llama-cpp-K2-FAST2 with Docker Model Runner:
docker model run hf.co/VladHong/llama-cpp-K2-FAST2
- Lemonade
How to use VladHong/llama-cpp-K2-FAST2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull VladHong/llama-cpp-K2-FAST2
Run and chat with the model
lemonade run user.llama-cpp-K2-FAST2-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Download scripts/make-release-summary.txt from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.5 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/scripts/make-release-summary.txt
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/scripts/make-release-summary.txt
-
curl -L -o make-release-summary.txt https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/scripts/make-release-summary.txt
1.5 kB
| Take a look at the changelog between the current version and the previous version - use the `./scripts/make-release-desc.sh [current-version]` to obtain it. | |
| Write a summary of the change log in a few sections: | |
| ``` | |
| ## Overview | |
| [an overview using 1 to 3 sentences (no line breaks)] | |
| ### API changes (if applicable) | |
| [summarize any API changes to `/include/*`, `/tools/mtmd/mtmd.h` and `/tools/server`] | |
| ### New models (if applicable) | |
| [summarize new models added to the `src/models/` directory] | |
| ### Core changes (if applicable) | |
| [summarize the changes to `/src/*` | |
| ### Multi-modality changes (if applicable) | |
| [summarize the changes to `/tools/mtmd/`] | |
| ### Server changes (if applicable) | |
| [summarize the changes to `/tools/server/`] | |
| ### UI changes (if applicable) | |
| [summarize the changes to `/tools/ui/`] | |
| ### ggml changes (if applicable) | |
| [if the version has been updated, link to the respective `ggml` releases on Github, f.ex `https://github.com/ggml-org/ggml/releases/tag/v0.22.0`. for each version bump, lookup the release description and copy the summary here] | |
| ``` | |
| Guidelines: | |
| - All bullet point in the summary should be concise and rarely exceed a single line of 120 characters | |
| - Avoid repeating `ggml`-specific changes - these should already be covered by the `ggml` release links | |
| - Provide PR link for each bullet point where possible | |
| - Don't add bullet point to state that there are no API changes in some module | |
| Output just the summary in a markdown block, without any extra text. | |